1. Technical Field
The present invention generally relates to a technical field of wireless communications of a Multiple-Input Multiple-Output (MIMO) scheme. More particularly, the present invention relates to a signal detection apparatus and a signal detection method used in a receiver for the MIMO scheme.
2. Background Art
In this kind of technical fields research and development are being promoted for realizing large-capacity high-speed information communications coming after current and next-generation techniques. For example, in addition to a Single-Input Single-Output (SISO) scheme, researches are being promoted for a Single-Input Multiple-Output (SIMO) scheme, a Multiple-Input Single-Output (MISO) and the Multiple-Input Multiple-Output (MIMO) scheme and the like from the viewpoint of increasing communications capacity.
FIG. 1 shows an outline of a communications system of the MIMO scheme including a transmitter 102 and a receiver 104. In the MIMO scheme, different signals are transmitted from transmission antennas 106-1˜N simultaneously with a same frequency. These transmission signals are received by receiving antennas 108-1˜N. Although, both of the number of the transmission antennas and the number of the receiving antennas are N for the sake of simplicity, they may be different. In the receiver 104, a process is performed for detecting each signal of a plurality of signals from the transmitter based on the received signals received by each receiving antenna. The detected signals are supplied to subsequent process components for performing further demodulation process.
There are several methods for signal detection performed in the receiver 104. One is a method called Maximum Likelihood Detection (MLD) method. In this method, a Euclidean distance or the square is calculated for every possible combination of the transmission signals transmitted from the transmission antennas and the received signal so as to select a combination of transmission signals that provides a minimum distance. According to this method, each signal of the transmission signals can be detected with reliability. But, there is a problem in that calculation load required for signal detection becomes large since it is necessary to calculate the squared Euclidean distance many times. For example, assuming that four transmission signals are transmitted from four transmission antennas using a 16QAM modulation scheme. In this case, since a transmission signal is mapped into any one of 16 constellation points, a total sum of combinations of transmission signals included in the received signal becomes (number of constellation points for one transmission signal)(number of transmission antennas)=164=65536. It requires very large calculation capacity to calculate the squared Euclidian distance for every combination so as to select a maximum likelihood combination, and, especially, downsizing of mobile terminals is inhibited. Further, when the calculation load is large, power consumption becomes large, which is especially disadvantageous for a small mobile terminal.
The QRM-MLD method is a signal detection method modified from the MLD method. In this method, QR decomposition and M algorithm are combined with the MLD method so as to try to decrease the number of times of calculations of the squared Euclidean distance. According to this method, in the above-mentioned assumed example, the number of times of the calculation can be decreased to (number of candidates of constellation points in a first stage)+(number of newly added candidates of constellation points)×(number of surviving candidates of constellation points in previous stage)×(number of transmission antennas)=16+16×16×3=784. The QRM-MLD method is described in the non-patent document 1, for example.
FIG. 2 shows a partial block diagram of a receiver that performs signal detection according to a conventional QRM-MLD method. For the sake of simplicity, four transmission signals x=(x1 . . . x4)T are transmitted from four transmission antennas respectively with the 16 QAM modulation scheme (the superscript T represents transpose). The receiver includes a plurality of receiving antennas 202-1, 202-2, 202-3 and 202-4, a channel estimation unit 204, a ranking unit 206, a reordering unit 208, a QR decomposition unit 210 a signal conversion unit 212, a maximum likelihood determination unit 214, and a likelihood output unit 215. The maximum likelihood determination unit 214 includes four determination units 216-1, 216-2, 216-3 and 216-4. The number of determination units is determined according to the number of transmission signals. Since each determination unit includes same process blocks, a fourth determination unit 216-4 is described as a representative. The determination unit includes a symbol replica generation unit 218-4, a squared Euclidian distance calculation unit 220-4 and a surviving symbol candidate selection unit 222-4.
The channel estimation unit 204 obtains a channel impulse response (CIR) or a channel estimation value based on a received signal including a pilot signal known in both sides of transmission and receiving. A matrix H having each channel estimation value hag as each matrix element is called a channel matrix, wherein hnm represents a channel estimation value between a m-th transmission antenna and a n-th receiving antenna, and, 1≦n, m≦4 holds true in the present example.
The ranking unit 206 rates or ranks a plurality of received signals y1, . . . , y4 in order of the size of power.
The reordering unit 208 reports arranging order of the received signals to the QR decomposition unit 210 and to the signal conversion unit 212.
The QR decomposition unit 210 obtains matrixes Q and R such that the channel matrix H obtained by the channel estimation unit 204 is represented as a product of a unitary matrix Q and an upper triangular matrix R (H=QR).
The signal conversion unit 212 multiplies a vector y=(y1 . . . y4)T having the received signals as its elements by a conjugate transpose matrix QH of the unitary matrix Q to perform signal conversion. The superscript H indicates conjugate transpose The relationship of y=Hx=QRx holds true between a transmission signal x and a received signal y. By multiplying this equation by QH from the left, the left side becomes QHy=z and the right side becomes QHQRx=Q−1QRx=Rx. Therefore, relationship between the transmission and received signals can be represented as z=Rx as follows, wherein z=(z1 . . . z4)T=QHy.

The relational express on can be also written as follows.z1=r11x1+r12x2+r13x3+r14x4 z2=r22x2+r23x3+r24x4 z3=r33x3+r34x4 z4=r44x4 
The maximum likelihood determination unit 214 narrows down symbol candidates of transmission signals using the maximum likelihood determination method (MLD method). The symbol replica generation unit 218-4 in the determination unit 216-4 generates symbol candidates of transmission signals corresponding to a received signal x4 using matrix elements of the upper triangular matrix R. The number of symbol candidates is c, for example.
The squared Euclidean distance calculation unit 220-4 calculates a squared Euclidean distance between the converted received signal zi and c symbol candidates. The squared Euclidian distance represents a metric on which calculation of likelihood is based. A symbol candidate for which small squared Euclidian distance is obtained is determined to be one near a transmitted symbol.
The surviving symbol candidate selection unit 222-4 outputs S1(≦C) symbol candidates as surviving symbol candidates based on the squared Euclidian distance for each candidate.
The likelihood output unit 215 calculates likelihood or reliability of the symbol candidates output from the surviving symbol candidate unit of the final stage. More particularly, the likelihood is represented as LLR (Log Likelihood Ratio). The output from the likelihood output unit 215 represents a signal detection result and is transmitted to a modulation unit (turbo decoder, for example) of a subsequent stage.
Operation is described next. The receiver receives transmission signals as received signals y1˜y4 with four antennas. These signals are supplied to the channel estimation unit 204 and the signal conversion unit 212. The order of the received signals are determined by the channel estimation unit 204, the ranking unit 206 and the reordering unit 208. In this example, the received signals are ordered in order of the size of received powers and it is assumed that received power becomes larger in order of x1, x2, x3 and x4. The received signals are converted such that z=(z1 . . . z4)T=QHy holds true by the signal conversion unit 212, and the converted signals are supplied to the maximum likelihood determination unit 214.
In a first stage in the maximum likelihood determination unit 214, a process corresponding to initial setting is performed in the determination unit 216-4. In this stage, the above equation on z4 is focused on. Since a matrix element r44 is known, it turns out that z4 depends only on one transmission signal x4. Therefore, the transmission signal x4 has 16 constellation point candidates at most. The symbol candidate generation unit 218-4 generates 16 (C=16) symbol candidates on x4. The squared Euclidian distance calculation unit 220-4 calculates squared Euclidian distances between each symbol candidate and the fourth received signal z4. Then, S1 symbol candidates are selected in ascending order of the distance as surviving symbol candidates.
A second stage is performed by the determination unit 216-3. In this stage, the equation on z3 is focused on. Matrix elements r33 and r34 are known, there are 16 candidates for x4, and also there are 16 constellation candidates for x3. As new constellation points on x3, 16 constellation points are introduced by the symbol generation unit 218-3. Therefore, there may be 16×16=256 combinations of constellation points. Thus, 256 squared Euclidian distances between each of these symbol candidates and the third received signal x3 are calculated, so that symbol candidates are narrowed down by selecting 16 (S2=16) candidates in ascending order of the value.
In a third stage, similar process is performed in the determination unit 216-2. In this stage, the equation on z2 is focused on. Matrix elements r22, r23 and r24 are known, combinations of transmission signals x3 and x4 are narrowed down to 16 candidates in the previous stage, and there are 16 constellation point candidates for x2. Therefore, the symbol candidate generation unit 218-2 generates 16 symbol candidates on x2. Also in this case, 16 (S3=16, candidates having small squared Euclidian distance are selected from among 256 constellation point combinations so as to narrow down symbol candidates.
In a fourth stage, similar process is performed in the determination unit 216-1. In this stage, the equation on z1 is focused on. Matrix elements r11, r12, r13 and r14 are known, combinations of transmission signals x2, x3 and x4 are narrowed down to 16 candidates in the previous stage, and there are 16 constellation point candidates for x1. Therefore, the symbol candidate generation unit 218-1 generates 16 symbol candidates on x1. In the fourth stage, 256 combinations of constellation points are output to the likelihood output unit 215.
Accordingly, by limiting the number of symbol candidates to equal to or less than a constant number (S1≦C and the like) in each stage, symbol candidates of transmission signals can be narrowed down without calculating squared Euclidian distances for all possible combinations of constellation points.
[Non-patent document 1] K. J. Kim, et al., “Joint channel estimation and data detection algorithms for MIMO-OFDM systems”, Proc. 36th Asilomar Conference on Signals, Systems and Computers, November 2002